This dataset represents the CHANGE in the number of jobs per industry category and sub-category from the previous month, not the raw counts of actual jobs. The data behind these monthly change values is from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

This layer shows figures of quit rates and quit levels by the US, BLS regions, and states. Data is from the Bureau of Labor Statistics (BLS) and was released October and November of 2021. The layer default symbology highlights to September 2021 quit rate in comparison to the national figure of 3.0%.According to the October 2021 News Release by BLS:"The number of quits increased in August to 4.3 million (+242,000). The quits rate increased to a series high of 2.9 percent. Quits increased in accommodation and food services (+157,000); wholesale trade (+26,000); and state and local government education (+25,000). Quits decreased in real estate and rental and leasing (-23,000). The number of quits increased in the South and Midwest regions."In the following November News Release:"In September, quits rates increased in 15 states and decreased in 10 states. The largest increases in quits rates occurred in Hawaii (+3.8 percentage points), Montana (+1.5 points), as well as Nevada and New Hampshire (+1.1 points each). The largest decreases in quits rates occurred in Kentucky (-1.1 percentage points), Iowa (-1.0 point), and South Dakota (-0.7 point). Over the month, the national quits rate increased (+0.1 percentage point)."Quit rates: The quits rate is the number of quits during the entire month as a percent of total employment.Quit levels: Quits are the number of quits during the entire month.State and US figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedRegion figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedThis data was obtained in October and November 2021, and the months of data from BLS are as follows:August 2020September 2020April 2021 (only offered for Regions)May 2021June 2021July 2021August 2021September 2021 (preliminary values)For the full data release, click here.The states (including the District of Columbia) that comprise the regions are: Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and VermontSouth: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West VirginiaMidwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and WisconsinWest: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

Graph and download economic data for Employed, Usually Work Full Time (LNS12500000) from Jan 1968 to Sep 2025 about full-time, 16 years +, household survey, employment, and USA.

Graph and download economic data for Unit Labor Costs for Transportation and Warehousing: General Freight Trucking (NAICS 4841) in the United States (IPUIN4841U100000000) from 1992 to 2024 about general, unit labor cost, freight, warehousing, trucks, NAICS, transportation, and USA.

Graph and download economic data for Expenditures: Cellular Phone Service by Number of Earners: Single Consumers, One Earner (CXU270102LB0703M) from 2010 to 2023 about phone, telecom, expenditures, consumer, services, and USA.

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels. Disclaimer: For information regarding future updates or preliminary/final data releases, please refer to the Bureau of Labor Statistics Release Calendar: https://www.bls.gov/cew/release-calendar.htm

Context

A striking graph from the Social Security Administration (https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.html) shows that median annual earnings for all men above the age of 20 have decreased since 1988: https://www.ssa.gov/policy/docs/factsheets/at-a-glance/earnings-men-1988-2018.svg" alt="">

I wanted to better understand how educational attainment has played a role in the above trend, and to come up with a model to forecast the future trend for earnings by educational attainment.

As I began looking at the data from the Bureau of Labor Statistics website, there was a striking trend: the median weekly earnings for all groups of people who did not have a bachelors degree or higher had decreased from 1979 levels, in constant 2020 dollars.

Content

I collated data from the US Bureau of Labor Statistics (https://www.bls.gov/webapps/legacy/cpsatab4.htm) and (https://www.bls.gov/cps/cpswktabs.htm) and the US Census Bureau (https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html) to create this dataset.

I have omitted details of gender and race, to solely look at the correlation between educational attainment and median weekly earnings over the years. All of the data is for ages 25 and higher unless otherwise stated in the column header.

An important note is that all the earnings data are in constant base 2020 dollars. This removes the effects of inflation and makes it possible to compare the numbers over the years.

The data starts at the year 1960, but unfortunately only overall labor force data, and population percentages of persons with a high school graduation (HSG) and persons with a Bachelors or Higher Degree are available. Median weekly earnings data categorized by educational attainment is available from 1979 onwards, while labor force data i.e., labor force level, labor force participation rate and the employment level by educational attainment is available only from 1992 onwards.

The only columns that have data from 1960 onwards are: (i) overall labor force level, (ii) civilian non-institutional population level, (iii) overall labor force participation rate, (iv) overall employment level, (v) overall percentage of high school graduates, and (vi) overall percentage of persons with a bachelors degree or higher.

Some of the columns can be calculated from other columns, for instance the civilian non-institutional population level can be calculated from the labor force participation rate.

Acknowledgements

All of this data is from the Bureau of Labor Statistics, and the Census Bureau: https://www.bls.gov/webapps/legacy/cpsatab4.htm , https://www.bls.gov/cps/cpswktabs.htm and https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-people.html .

A big thank you to all those who worked so hard to collect and organize this data.

Inspiration

The main question is: what is the best way to generate forecasts for median weekly earnings for each educational attainment level?

The Work Stoppages program provides monthly and annual data and analysis of major work stoppages involving 1,000 or more workers lasting one full shift or longer. The monthly and annual data show the establishment and union(s) involved in the work stoppage along with the location, the number of workers and the days of idleness. The monthly data list all work stoppages involving 1,000 or more workers that occurred during the full calendar month for each month of the year. The annualized data provide statistics, analysis and details of each work stoppage of 1,000 or more workers that occurred during the year. The work stoppages data are gathered from public news sources, such as newspapers and the Internet. The BLS does not distinguish between strikes and lock-outs in the data; both are included in the term "work stoppages". For more information and data visit: https://www.bls.gov/wsp/

The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible. The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series. The OEWS estimates are published annually. SOURCE: https://www.bls.gov/oes/oes_emp.htm

Graph and download economic data for Consumer Unit Characteristics: Number of People in CU by Size of Consumer Unit: Four People in Consumer Unit (CXU980010LB0506M) from 1984 to 2023 about consumer unit, persons, and USA.

Graph and download economic data for Expenditures: Residential Phone Service, VOIP, and Phone Cards by Number of Earners: Single Consumers, One Earner (CXURESPHONELB0703M) from 2013 to 2023 about phone, telecom, residential, expenditures, consumer, services, and USA.

Graph and download economic data for Employment for Transportation and Warehousing: General Freight Trucking (NAICS 4841) in the United States (IPUIN4841W010000000) from 1987 to 2024 about general, freight, warehousing, trucks, NAICS, transportation, employment, and USA.

Graph and download economic data for All Employees, Federal (CES9091000001) from Jan 1939 to Sep 2025 about establishment survey, federal, government, employment, and USA.

Graph and download economic data for Consumer Unit Characteristics: Number of People in CU by Generation: Birth Year from 1928 to 1945 (CXU980010LB1605M) from 2016 to 2018 about consumer unit, birth, persons, and USA.

Graph and download economic data for Employed full time: Wage and salary workers: Pest control workers occupations: 16 years and over (LEU0254494500A) from 2000 to 2024 about occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

Graph and download economic data for All Employees, Health Care (CES6562000101) from Jan 1990 to Sep 2025 about health, establishment survey, education, services, employment, and USA.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Sep 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Graph and download economic data for Civilian Labor Force Level (CLF16OV) from Jan 1948 to Sep 2025 about civilian, 16 years +, labor force, labor, household survey, and USA.

Graph and download economic data for Multiple Jobholders as a Percent of Employed (LNS12026620) from Jan 1994 to Sep 2025 about multiple jobholders, 16 years +, percent, household survey, employment, and USA.

Graph and download economic data for Average Weekly Hours of All Employees, Total Private (AWHAETP) from Mar 2006 to Sep 2025 about establishment survey, hours, private, employment, and USA.